教学课程资源库 更多>>

关键词： Social networking (online)   Computational modeling   Query processing   Knowledge engineering   Formal concept analysis   Computer science   Quality control   Clique   formal concept analysis (FCA)   fuzzy attributed social network   skyline  

摘要： Identifying the optimal groups of users that are closely connected and satisfy some ranking criteria from an attributed social network attracts significant attention from both academia and industry. Skyline query processing, a multicriteria decision-making optimized technique, is recently embedded into cohesive subgraphs mining in graphs/social networks. However, the existing studies cannot capture the fuzzy property of connections between users in social networks. To fill this gap, in this article, we formulate a novel model of the skyline (lambda,k)-cliques over a fuzzy attributed social network and develop a formal concept analysis (FCA)-based skyline (lambda,k)-cliques identification algorithm. Specifically, lambda can be regarded as a quality control parameter for measuring the stability of the cohesive groups. Extensive experimental results conducted on three real-world datasets demonstrate the effectiveness of the skyline (lambda,k)-clique model in a fuzzy attributed social network. Furthermore, an illustrative example is executed for revealing the usefulness of our model. It is expected that our proposed skyline (lambda,k)-clique model can be widely used in various graph-based computational social systems, such as optimal team formation in crowdsourcing, and group recommendation in social networks.

关键词： Convolution   Shape   Computer architecture   Computational modeling   Lenses   Redundancy   Computer science   Channelwise attention   convolutional networks   grouped relationships   inner-imaging (InI)  

摘要： Despite the tremendous success in computer vision, deep convolutional networks suffer from serious computation costs and redundancies. Although previous works address that by enhancing the diversities of filters, they have not considered the complementarity and the completeness of the internal convolutional structure. To respond to this problem, we propose a novel inner-imaging (InI) architecture, which allows relationships between channels to meet the above requirement. Specifically, we organize the channel signal points in groups using convolutional kernels to model both the intragroup and intergroup relationships simultaneously. A convolutional filter is a powerful tool for modeling spatial relations and organizing grouped signals, so the proposed methods map the channel signals onto a pseudoimage, like putting a lens into the internal convolution structure. Consequently, not only is the diversity of channels increased but also the complementarity and completeness can be explicitly enhanced. The proposed architecture is lightweight and easy to be implement. It provides an efficient self-organization strategy for convolutional networks to improve their performance. Extensive experiments are conducted on multiple benchmark datasets, including CIFAR, SVHN, and ImageNet. Experimental results verify the effectiveness of the InI mechanism with the most popular convolutional networks as the backbones.

关键词： app development   behavior change technique   health promotion   mobile health   mobile application   application development   design platform   platform development   no-code mHealth app   no-code app   no-code   end user   participatory research   Pathverse   agile   hybrid-agile   software design   software development   software developer   computer science   BCT   behavior change   research tool   research instrument   digital platform   mHealth   mobile app  

摘要： Background: A challenge facing researchers conducting mobile health (mHealth) research is the amount of resources required to develop mobile apps. This can be a barrier to generating relevant knowledge in a timely manner. The recent rise of "no-code" software development platforms may overcome this challenge and enable researchers to decrease the cost and time required to develop mHealth research apps. Objective: We aimed to describe the development process and the lessons learned to build Pathverse, a no-code mHealth app design platform. Methods: The study took place between November 2019 and December 2021. We used a participatory research framework to develop the mHealth app design platform. In phase 1, we worked with researchers to gather key platform feature requirements and conducted an exploratory literature search to determine needs related to this platform. In phase 2, we used an agile software framework (Scrum) to develop the platform. Each development sprint cycle was 4 weeks in length. We created a minimum viable product at the end of 7 sprint cycles. In phase 3, we used a convenience sample of adults (n=5) to gather user feedback through usability and acceptability testing. In phase 4, we further developed the platform based on user feedback, following the V-model software development process. Results: Our team consulted end users (ie, researchers) and utilized behavior change technique taxonomy and behavior change models (ie, the multi-process action control framework) to guide the development of features. The first version of the Pathverse platform included features that allowed researchers to (1) design customized multimedia app content (eg, interactive lessons), (2) set content delivery logic (eg, only show new lessons when completing the previous lesson), (3) implement customized participant surveys, (4) provide self-monitoring tools, (5) set personalized goals, and (6) customize app notifications. Usability and acceptability testing revealed that r

关键词： Data mining   Systematics   Manuals   Libraries   Education   Licenses   Programming profession   Computer Science Education (CSEd)   open educational resources (OERs)   OER classification   OER digital source  

摘要： Contribution: This study presents the results of a systematic mapping on the classification and organization of open educational resources (OERs) focused on Computer Science Education (CSEd) in digital sources. Background: The number of open resources (e.g., images, videos, and websites) available on the Internet for the teaching of Computer Science has increased in recent years. As a consequence, several authors have proposed different ways of classifying them, which include lists of disciplines, classification algorithms, and semantic enrichment. However, such studies are dispersed and fragmented in the literature, making the current state-of-the-art unclear. Research Questions: 1) What digital sources have been used to classify OERs for CSEd? 2) What CSEd domains have been explored for the classification of OERs? and 3) What approaches have been adopted for the classification of OERs for CSEd? Methodology: Three search strategies were performed: 1) automatic search in the five major digital libraries of CSEd;2) manual search in the major CSEd conferences and journals;and 3) snowballing on the references and citations. As a result, 22 relevant studies were selected. Findings: The main findings were systematization of the main OER sources for CSEd, identification of 64 CSEd domains covered by OERs organized in a taxonomy, the immaturity level of investigations and tools, and lack of mechanisms that organize OERs for CSEd.

关键词： Task analysis   Optimization   Knowledge transfer   Sociology   Evolutionary computation   Multitasking   Computer science   Evolutionary multitasking (EMT)   helper-task   knowledge transfer   multifactorial evolutionary algorithm (MFEA)   multiobjectivization   multiobjectivization via decomposition (MVD)  

摘要： Evolutionary multitasking (EMT) is an emerging research direction in the field of evolutionary computation. EMT solves multiple optimization tasks simultaneously using evolutionary algorithms with the aim to improve the solution for each task via intertask knowledge transfer. The effectiveness of intertask knowledge transfer is the key to the success of EMT. The multifactorial evolutionary algorithm (MFEA) represents one of the most widely used implementation paradigms of EMT. However, it tends to suffer from noneffective or even negative knowledge transfer. To address this issue and improve the performance of MFEA, we incorporate a prior-knowledge-based multiobjectivization via decomposition (MVD) into MFEA to construct strongly related meme helper-tasks. In the proposed method, MVD creates a related multiobjective optimization problem for each component task based on the corresponding problem structure or decision variable grouping to enhance positive intertask knowledge transfer. MVD can reduce the number of local optima and increase population diversity. Comparative experiments on the widely used test problems demonstrate that the constructed meme helper-tasks can utilize the prior knowledge of the target problems to improve the performance of MFEA.

关键词： Web services   Robustness   Computer science   Collaboration   Social networking (online)   Recommender systems   Proposals   Cold-start problems   collaborative filtering (CF)   rating prediction   recommendation   user trust  

摘要： The ever-increasing popularity of recommendation systems allows users to find appropriate services without excessive effort. However, due to the unstable and complex network environment, the historical behavior data of users are quite sparse in most cases. The inherent drawbacks render preference prediction infeasible for cold-start users and have become a crucial issue to be resolved in recommendation systems. To deal with the problems, we first present a Trust-based Collaborative Filtering (TbCF) algorithm to perform basic rating prediction in a manner consistent with the existing CF methods. Then, we propose the Hybrid Collaborative Filtering Recommendation approach with User-Item-Trust Records (UIThybrid), a novel approach that incorporates user trust into the existing CF-based methods in a harmonious way to supplement rating information. UIThybrid employs multiple perspectives to extract proper services and achieves a good tradeoff between the robustness, accuracy, and diversity of the recommendation. We conduct extensive real-world experiments on the Epinions data set to demonstrate the feasibility and efficiency of UIThybrid.

关键词： capital punishment   Marshall hypothesis   public opinion  

摘要： As we approach the 50-year anniversary of the landmark Furman decision, the time is ripe for a renewed empirical test of the hypotheses Justice Marshall presented in his concurring opinion. Most relevant to this study, he suggested in his second proposition that "people who were fully informed as to the purposes of the penalty and its liabilities would find the penalty, shocking, unjust and unacceptable." While there has been much empirical testing of this hypothesis, the intent of this study is to add to the existing literature by examining whether specific types of information about capital punishment is associated with opposition to capital punishment. Data were collected by an instructor who taught death penalty classes (n = 122 subjects) to test this hypothesis. Results provide qualified support for Marshall's second hypothesis that knowledge is significantly related to an increase in death penalty opposition. Moreover, the following factors were significant predictors of overall change in participants' opinion: cost, deterrence, race of victim, and evolving societies. Surprisingly, the innocence items did not appear statistically significant in altering opinions. Future research should continue to explore further aspects of the Marshall hypothesis such as the effect of different methods of information delivery.

关键词： Systematics   Engineering profession   Statistics   Software   Sociology   Information technology   Computer science   Computer science (CS)   educational interventions (EIs)   female students   Latin America   women  

摘要： Contributions: The underrepresentation of women in computer science (CS) majors has long been a focus of attention in many academic documents, the majority of them from the United States and Europe. There is, however, a lack of information about educational interventions (EIs) for women in computing in Latin America. The contribution of this article is to cover this gap and describe what researchers in Latin American countries have been publishing about the recruitment and retention of women in the CS field.

关键词： Culturally authentic pedagogy   High school computer science   K-12 computer science   Student agency  

摘要： This study explores student agency in the context of a culturally authentic computer science (CS) curriculum implemented in an introductory CS course in two high schools. Drawing on focus group and interview data, the study utilizes qualitative research methods to examine how students exercise critical agency as they engage in the course and how the curriculum supports student agency. Findings suggest three ways in which the curriculum served as a context for student agency: (1) gaining CS knowledge and skills that students then apply to address real-world needs and problems, (2) creating opportunities to “try-on” or improvise new identities and/or envision “future selves” in CS, and (3) engaging in personally relevant project work that leverages assets students brought to their experience with the curriculum. Implications for CS education research and practice are discussed. © 2022, The Author(s).

关键词： Privacy   Protocols   Entropy   Computer science   Task analysis   Probabilistic logic   Data mining   Privacy amplification   tamperable memory   randomness extractors   non-malleability  

摘要： We extend the classical problem of privacy amplification to a setting where the active adversary, Eve, is also allowed to fully corrupt the internal memory (which includes the shared randomness, and local randomness tape) of one of the honest parties, Alice and Bob, before the execution of the protocol. We require that either one of Alice or Bob detects tampering, or they agree on a shared key that is indistinguishable from the uniform distribution to Eve. We obtain the following results: 1) we give a privacy amplification protocol via low-error non-malleable two-source extractors with one source having low min-entropy. In particular, this implies the existence of such (non-efficient) protocols;2) we show that even slight improvements to the state-of-the-art explicit non-malleable two-source extractors would lead to explicit low-error, low min-entropy two-source extractors, thereby resolving a long-standing open question. This suggests that obtaining (information-theoretically secure) explicit non-malleable two-source extractors for (1) might be hard;3) we present explicit constructions of low-error, low min-entropy non-malleable two-source extractors in the CRS model of (Garg, Kalai, Khurana, Eurocrypt 2020), assuming either the quasi-polynomial hardness of DDH or the existence of nearly-optimal collision-resistant hash functions;4) we instantiate our privacy amplification protocol with the above mentioned non-malleable two-source extractors in the CRS model, leading to explicit, computationally-secure protocols. This is not immediate from (1) because in the computational setting we need to make sure that, in particular, all randomness sources remain samplable throughout the proof. This requires upgrading the assumption of quasi-polynomial hardness of DDH to sub-exponential hardness of *** emphasize that each of the first three results can be read independently.